Such a product as a PC is formed of a plurality of components (a CPU, a memory, an HDD, etc.). In general, each component is selected from a plurality of categories of components (in the case of, for example, a memory, it is selected from memories of 512 MB, 1024 MB, etc.). When designing such a product as the above, different product numbers are assigned to different combinations of components. However, a plurality of component combinations that have the same product number may exist. In general, the correspondence of the component combinations and the product numbers is shown in a table (hereinafter referred to as a component combination table). In this case, however, the larger the number of components categories and the number of components, the larger the number of combinations thereof and therefore the worse the readability of the table. To avoid this, there is a method of expressing the correspondence between the component combinations and the product numbers in the form of a determination tree in which labels at leaves correspond to product numbers, and labels at the other points (nodes) correspond to component categories, based on which classification of components is performed. In the case of expressing the correspondence using a determination tree, the size (i.e., the number of points (nodes)) of the tree varies depending upon the component category, based on which classification of components is made. As one method of generating a determination tree of a small size, there is a method of determining the categories of classified components utilizing ID3 algorithm (see, for example, J. R. Quinlan, Machine Learning 1 “Induction of Decision Trees,” p 81-p 106 1986).
The larger the number of combinations of components, the larger the size of the component combination table, which makes it troublesome to search for the table to detect a product number corresponding to a particular component combination. If a determination tree is used, a target product number can be detected by tracing the tree from the root to the branch corresponding to a target product. However, even in the case of using the determination tree, if the number of nodes is increased, the depth of the tree is generally increased, which requires a lot of time and labor to detect the product number. Therefore, if a determination tree, which uses a smaller number of nodes to express the same content, is employed, the target product number can be more easily detected.